Name: Retrieval Augmented Generation (RAG)
Brand: DeepLearning.AI
Availability: OnlineOnly
Rating: 4.8 (28 reviews)

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Learner Reviews & Feedback for Retrieval Augmented Generation (RAG) by DeepLearning.AI

4.8

stars

107 ratings

About the Course

Retrieval Augmented Generation (RAG) improves large language model (LLM) responses by retrieving relevant data from knowledge bases—often private, recent, or domain-specific—and using it to generate more accurate, grounded answers. In this course, you’ll learn how to build RAG systems that connect LLMs to external data sources. You’ll explore core components like retrievers, vector databases, and language models, and apply key techniques at both the component and system level. Through hands-on work with real production tools, you’ll gain the skills to design, refine, and evaluate reliable RAG pipelines—and adapt to new methods as the field advances. Across five modules, you'll complete hands-on programming assignments that guide you through building each core part of a RAG system, from simple prototypes to production-ready components. Through hands-on labs, you’ll: - Build your first RAG system by writing retrieval and prompt augmentation functions and passing structured input into an LLM. - Implement and compare retrieval methods like semantic search, BM25, and Reciprocal Rank Fusion to see how each impacts LLM responses. - Scale your RAG system using Weaviate and a real news dataset—chunking, indexing, and retrieving documents with a vector database. - Develop a domain-specific chatbot for a fictional clothing store that answers FAQs and provides product suggestions based on a custom dataset. - Improve chatbot reliability by handling real-world challenges like dynamic pricing and logging user interactions for monitoring and debugging. - Develop a domain-specific chatbot using open-source LLMs hosted by Together AI for a fictional clothing store that answers FAQs and provides product suggestions based on a custom dataset. You’ll apply your skills using real-world data from domains like media, healthcare, and e-commerce. By the end of the course, you’ll combine everything you’ve learned to implement a fully functional, more advanced RAG system tailored to your project’s needs....

Top reviews

Aug 13, 2025

I learnt quite a bit about LLMs, vector databases, RAG and various terms associated with this space. I came out better informed and hopefully learn more and implement these things in my projects

Aug 27, 2025

I believe the course covers alot of ground and provides good depth for each component. This will definitely provide solid foundation to anyone who was worked with LLMs in the past

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26 - 30 of 30 Reviews for Retrieval Augmented Generation (RAG)

By Rajesh I

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Aug 25, 2025

Gave good understanding on RAG.

By Omar

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Aug 29, 2025

What a GRATE course to have !!

By Santiago S

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Oct 3, 2025

The instructor and lessons were excellent. It is also a highly relevant course for today's software engineers. However, I think more attention should be put to the Jupyter Notebook tasks. One had a bug that prevented correct grading (which affected my course final grade), and another had a bug that made impossible to do one part of the assignment. One even had factually incorrect information. Even with this challenges, I am happy I took this course. I did learn a lot and it was a very rewarding and productive use of my time.